package net.bwie.jtp.dwd.log.job;


import com.alibaba.fastjson.JSON;
import net.bwie.jtp.dwd.log.function.AdjustIsNewProcessFunction;
import net.bwie.jtp.dwd.log.function.LogSplitProcessFunction;
import net.bwie.realtime.jtp.common.utils.KafkaUtil;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;
import org.apache.flink.util.OutputTag;

public class JtpLogEtlJob {
    public static void main(String[] args) throws Exception {
        //1.执行环境-evn
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);


        //2.数据源-source
        DataStream<String> kafkaDataStream = KafkaUtil.consumerKafka(env, "topic-log");

        kafkaDataStream.print("kafka");

        //3.数据源转换-transformation
        //4.数据输出-sink
        processLog(kafkaDataStream);
        //5.执行-execute
        env.execute("JtpLogEtlJob");
    }


    private static void processLog(DataStream<String> logStream) {
        //1-数据清洗
        DataStream<String> jsonStream = logCleaned(logStream);


        //2-新老访客状态标记修复
        DataStream<String> etlStream = processIsNew(jsonStream);
        // etlStream.print();


        //3-数据分流
        DataStream<String> pageStream = splitStream(etlStream);
        // pageStream.print();


        // 4-存储数据
        KafkaUtil.producerKafka(pageStream, "dwd-traffic-page-log");
    }


    /*
    3-数据分流
     */
    private static DataStream<String> splitStream(DataStream<String> jsonStream) {
    //todo 测流输出标记
        final OutputTag<String> errorTag = new OutputTag<String>("error-log"){};
        final OutputTag<String> startTag = new OutputTag<String>("start-log"){};
        final OutputTag<String> displayTag = new OutputTag<String>("display-log"){};
        final OutputTag<String> actionTag = new OutputTag<String>("action-log"){};

    //todo 第一步 日志分流处理
        SingleOutputStreamOperator<String> pageStream = jsonStream.process(
                new LogSplitProcessFunction(errorTag, startTag, displayTag, actionTag)
        );

        //todo 第二步 分流输出
        DataStream<String> errorStream = pageStream.getSideOutput(errorTag);
        KafkaUtil.producerKafka(errorStream, "dwd-traffic-error-log");
        DataStream<String> startStream = pageStream.getSideOutput(startTag);
        KafkaUtil.producerKafka(startStream, "dwd-traffic-start-log");
        DataStream<String> displayStream = pageStream.getSideOutput(displayTag);
        KafkaUtil.producerKafka(displayStream, "dwd-traffic-display-log");
        DataStream<String> actionStream = pageStream.getSideOutput(actionTag);
        KafkaUtil.producerKafka(actionStream, "dwd-traffic-action-log");

        //todo 第三部输出主流
         return pageStream;
    }




    //2-新老访客状态标记修复
    private static DataStream<String> processIsNew(DataStream<String> jsonStream) {

        //a-按照设备id进行分组
        KeyedStream<String, String> midStream = jsonStream.keyBy(new KeySelector<String, String>() {
            @Override
            public String getKey(String value) throws Exception {
                return JSON.parseObject(value).getJSONObject("common").getString("mid");
            }
        });

        //b-状态编程，对is_new检验

        SingleOutputStreamOperator<String> isNewStream = midStream.process(new AdjustIsNewProcessFunction());
        return isNewStream;
    }


    //1-数据清洗
    private static DataStream<String> logCleaned(DataStream<String> logStream) {

        //a-脏数据的侧边流输出时的标记
        final OutputTag<String> dirtyTag = new OutputTag<String>("dirty-log"){};

        //b-数据清洗处理
        SingleOutputStreamOperator<String> cleanedStream = logStream.process(new ProcessFunction<String, String>() {
            @Override
            public void processElement(String value, Context ctx, Collector<String> out) throws Exception {
                try {
                    //a 解析json数据
                    JSON.parseObject(value);
                    //b.没有异常，解析正确，正常输出
                    out.collect(value);
                } catch (Exception e) {
                    //c.有异常，输出到侧边流
                    ctx.output(dirtyTag, value);
                }
            }
        });

        //c-测流输出
        DataStream<String> dirtyStream = cleanedStream.getSideOutput(dirtyTag);
        KafkaUtil.producerKafka(dirtyStream, "dwd-traffic-dirty-log");

        //d-返回正常数据
        return cleanedStream;
    }

}
